arXiv AI
Aug 11
ColluSkill: Adversarial Cross-Skill Composition for Evading Agent Skill Scanners
arXiv:2608. 09732v1 Announce Type: cross Abstract: Agent skills are emerging as an important attack surface in LLM-based agent systems.
SkillJect: Effectively Automating Skill-Based Prompt Injection for Skill-Enabled Agents
arXiv:2602. 14211v3 Announce Type: replace-cross Abstract: Agent skills extend LLM agents with task-specific instructions, executable scripts, and auxiliary resources, improving reusability but creating a new supply-chain attack surface.
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arXiv AI
22h ago
TRUSS: Towards Task-Reliable and User-Safe Automated Agent Skill Generation
arXiv:2608. 17588v1 Announce Type: new Abstract: Agent Skills package reusable natural language procedures with executable resources, enabling software agents to acquire task specific capabilities without model adaptation.
Hugging Face Trending Papers
1d ago
TRUSS: Towards Task-Reliable and User-Safe Automated Agent Skill Generation
Agent Skills package reusable natural language procedures with executable resources, enabling software agents to acquire task specific capabilities without model adaptation. Automatically generating such Skills can improve task performance, yet evaluating a candidate solely from its artifact or final task outcome leaves unresolved which actions the equipped agent will perform and which side effects those actions will produce.
arXiv AI
Jun 9
POISE: Position-Aware Undetectable Skill Injection on LLM Agents
arXiv:2606. 07943v1 Announce Type: cross Abstract: Agent skills provide a lightweight mechanism for extending general-purpose agents, but their open format exposes them to skill-poisoning attacks.
arXiv AI
Aug 11
ElasticBack: Stealthy Conditional Backdoor in LLM-Agent Skills via Coupled Trigger-Rule Optimization
arXiv:2608. 09577v1 Announce Type: new Abstract: Agent skills, bundles of instructions and resources that an LLM agent loads on demand, form an emerging supply chain where a single poisoned skill can persistently compromise every agent that installs it.
arXiv AI
Jun 2
Defenses & Enablers For Skill Injection Attacks on Terminal Based Agents
arXiv:2606. 01567v1 Announce Type: cross Abstract: Large language model (LLM) agents increasingly rely on reusable skills i.
arXiv AI
Jun 16
Benign in Isolation, Harmful in Composition: Security Risks in Agent Skill Ecosystems
arXiv:2606. 15242v1 Announce Type: cross Abstract: Skills are becoming the capability layer through which LLM agents turn plans into actions, but their use introduces security risks such as data leakage, unauthorized operations, and tool misuse.
arXiv AI
Aug 11
SkillsMetric: Mapping the Detection Boundary of Static Analysis for Malicious Agent Skills
arXiv:2608. 08468v1 Announce Type: cross Abstract: Agent Skills---structured packages of instructions and scripts that augment LLM-based agents---are rapidly proliferating, yet their security properties remain under-explored.
arXiv AI
Aug 12
Poise: Position-Aware One-Instruction Skill Injection for Silent Execution on LLM Agents
arXiv:2606. 07943v2 Announce Type: replace-cross Abstract: Agent skills extend general-purpose agents, but their open format enables skill poisoning: a tampered skill can make an agent run an attacker's command while completing the user's legitimate task.
arXiv AI
Aug 11
Query-Only Backdoor Attacks on Self-Evolving Skills via Trajectory Poisoning
arXiv:2608. 08303v1 Announce Type: new Abstract: Agentic skills improve large language model (LLM) agents by encoding reusable procedures for complex tasks.
arXiv AI
Jun 2
Benchmarking Security Risk Detection and Verification in Open Agentic Skill Ecosystems
arXiv:2606. 00925v1 Announce Type: cross Abstract: Open agent platforms allow community contributors to publish reusable skills that agents can invoke at runtime.
arXiv AI
Aug 7
When Experience Becomes Instruction: Trajectory Poisoning in Self-Evolving Agent Skill Systems
arXiv:2608. 05563v1 Announce Type: cross Abstract: Self-evolving skill (SES) systems distill agent trajectories into persistent skills, allowing untrusted experience to become trusted instruction.